The authors argue that 4K instruction-driven image editing is a system problem rather than a single-model problem.
Native 4K image editing works better as an agent system than a single model
BluePixel pairs an efficient 4K training recipe with a verifier-driven agent harness and ranks second only to GPT Image 2 on a native-4K benchmark.
Independent
Shanyan Guan · Shiyu Li · Xin Li · Zhizhou Chen · Yunzhe Xu · Yuehao Liu · +14 more
Research Digest··3 min read
The authors present BluePixel, a native-4K editing model coupled with an agent harness, and disclose a training recipe that upgrades a 1K editor to 4K without pretraining from scratch.
Why this paper
Independent
In one line
BluePixel combines an efficiently adapted native-4K editor with specialist routing and reward-based retries, delivering four-step 4K edits while ranking second on VINS-4KEval++.
What we could check
- ·No code link found
- ·No weights link found
- ·No dataset link found
- ✓Compute or model size stated (hardware Kunlunxin P800 XPU)
- ·No stated limitations found
- ✓Reports numbers on named benchmarks
Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.
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